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CONSEQUENCES - The 2nd Workshop on Causality, Counterfactuals and Sequential Decision-Making for Recommender Systems.

, , , , , and . RecSys, page 1223-1226. ACM, (2023)

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Meta-Prod2Vec - Product Embeddings Using Side-Information for Recommendation., , and . CoRR, (2016)REVEAL 2020: Bandit and Reinforcement Learning from User Interactions., , , , , and . RecSys, page 628-629. ACM, (2020)Improving Offline Contextual Bandits with Distributional Robustness., , and . CoRR, (2020)Learning a Named Entity Tagger from Gazetteers with the Partial Perceptron., , and . AAAI Spring Symposium: Learning by Reading and Learning to Read, page 7-13. AAAI, (2009)RecoGym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising., , , , and . CoRR, (2018)Resolving Surface Forms to Wikipedia Topics., , , , and . COLING, page 1335-1343. Tsinghua University Press, (2010)DLRS 2018: third workshop on deep learning for recommender systems., , , , , , and . RecSys, page 512-513. ACM, (2018)Neural Generative Models for Global Optimization with Gradients., , , and . CoRR, (2018)Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions., , and . ADKDD@KDD, page 8:1-8:6. ACM, (2017)Three Methods for Training on Bandit Feedback., , and . CoRR, (2019)